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VAR Priors: Success or lack of a decent macroeconomic theory?

  • Francisco F. R. Ramos

    (Faculty of Economics, University of Porto, Portugal)

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    The purpose of this paper is to demonstrate that the success of the Litterman prior in VAR forecasting is not due to the realism of the prior, but rather because the prior conveniently reduces forecast error variance in common cases of misspecification. Specifically, it is shown that the imposition of a random walk prior reduces forecast error variance in misspecifications involving (1) time-varying coefficients misspecified as constant coefficients, (2) serially correlated residuals misspecified as white noise, and (3) the inclusion of an irrelevant unit root process in VAR.

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    Paper provided by EconWPA in its series Econometrics with number 9601002.

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    Length: 18 pages
    Date of creation: 22 Jan 1996
    Date of revision:
    Handle: RePEc:wpa:wuwpem:9601002
    Note: Type of Document - word for windows 2.0; prepared on IBM PC ; to print on HP/Epson; pages: 18 ; figures: none. Word for Windows document submitted by ftp
    Contact details of provider: Web page: http://econwpa.repec.org

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    1. Fair, Ray C, 1979. "An Analysis of the Accuracy of Four Macroeconometric Models," Journal of Political Economy, University of Chicago Press, vol. 87(4), pages 701-18, August.
    2. Christopher A. Sims, 1982. "Policy Analysis with Econometric Models," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 13(1), pages 107-164.
    3. McNees, Stephen K, 1986. "Forecasting Accuracy of Alternative Techniques: A Comparison of U.S. Macroeconomic Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 5-15, January.
    4. Christopher A. Sims, 1986. "Are forecasting models usable for policy analysis?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-16.
    5. Robert B. Litterman, 1984. "Specifying vector autoregressions for macroeconomic forecasting," Staff Report 92, Federal Reserve Bank of Minneapolis.
    6. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
    7. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1986. "Forecasting and conditional projection using realistic prior distribution," Staff Report 93, Federal Reserve Bank of Minneapolis.
    8. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    9. Robert B. Litterman, 1985. "Forecasting with Bayesian vector autoregressions five years of experience," Working Papers 274, Federal Reserve Bank of Minneapolis.
    10. Lucas, Robert Jr, 1976. "Econometric policy evaluation: A critique," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 1(1), pages 19-46, January.
    11. Robert B. Litterman, 1979. "Techniques of forecasting using vector autoregressions," Working Papers 115, Federal Reserve Bank of Minneapolis.
    12. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-44, January.
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